Agent-based resource discovery in cloud computing using bloom filters

Regarding the fact that, there are large number of resources in cloud computing system. Developing effective solutions for their queries are very important. The success of cloud computing systems fundamentally relies on the efficient use of resources. Discovering and managing resources is one important step in the system effecting. In this paper, a method of Agent-based resource discovery using Bloom filter is proposed. In this strategy, resources information are stored in a Bloom filter, and then, the Bloom filter is sent to the related broker agent and broker agent sends it to the related database. In addition, users make their requests using their hash values and send them to related broker agent. The information needed for search and discovery is stored inside the Bloom filters and then the achieved Bloom filter is transferred, therefore, the amount data transmitted is reduced significantly. The results show that, in the proposed approach, the number of transferred bits in the network for user's requests, the number of transferred bits in the network for resources information, and the average of consumed time to search and discovery requested resources, approximately are 5 times, 15 times, and 3 times less than the case without using Bloom filter, respectively. The consumed memory, used bandwidth in the network, the time of search and discovery of resources, have improved significantly.